Overview

Brought to you by YData

Dataset statistics

Number of variables8
Number of observations541909
Missing cells136534
Missing cells (%)3.1%
Duplicate rows4879
Duplicate rows (%)0.9%
Total size in memory173.1 MiB
Average record size in memory335.0 B

Variable types

Text3
Numeric3
DateTime1
Categorical1

Alerts

Dataset has 4879 (0.9%) duplicate rowsDuplicates
Country is highly imbalanced (85.9%)Imbalance
CustomerID has 135080 (24.9%) missing valuesMissing
UnitPrice is highly skewed (γ1 = 186.5069717)Skewed

Reproduction

Analysis started2025-10-23 19:49:56.776281
Analysis finished2025-10-23 19:50:05.740093
Duration8.96 seconds
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

Distinct25900
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size28.4 MiB
2025-10-23T21:50:05.972796image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0171449
Min length6

Characters and Unicode

Total characters3260745
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5841 ?
Unique (%)1.1%

Sample

1st row536365
2nd row536365
3rd row536365
4th row536365
5th row536365
ValueCountFrequency (%)
5735851114
 
0.2%
581219749
 
0.1%
581492731
 
0.1%
580729721
 
0.1%
558475705
 
0.1%
579777687
 
0.1%
581217676
 
0.1%
537434675
 
0.1%
580730662
 
0.1%
538071652
 
0.1%
Other values (25890)534537
98.6%
2025-10-23T21:50:06.307143image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5866996
26.6%
7358618
11.0%
6339129
 
10.4%
4324436
 
9.9%
8248810
 
7.6%
3247661
 
7.6%
0224299
 
6.9%
1219402
 
6.7%
9214831
 
6.6%
2207272
 
6.4%
Other values (2)9291
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)3260745
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5866996
26.6%
7358618
11.0%
6339129
 
10.4%
4324436
 
9.9%
8248810
 
7.6%
3247661
 
7.6%
0224299
 
6.9%
1219402
 
6.7%
9214831
 
6.6%
2207272
 
6.4%
Other values (2)9291
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)3260745
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5866996
26.6%
7358618
11.0%
6339129
 
10.4%
4324436
 
9.9%
8248810
 
7.6%
3247661
 
7.6%
0224299
 
6.9%
1219402
 
6.7%
9214831
 
6.6%
2207272
 
6.4%
Other values (2)9291
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)3260745
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5866996
26.6%
7358618
11.0%
6339129
 
10.4%
4324436
 
9.9%
8248810
 
7.6%
3247661
 
7.6%
0224299
 
6.9%
1219402
 
6.7%
9214831
 
6.6%
2207272
 
6.4%
Other values (2)9291
 
0.3%
Distinct4070
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size28.0 MiB
2025-10-23T21:50:06.588524image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.0868448
Min length1

Characters and Unicode

Total characters2756607
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique233 ?
Unique (%)< 0.1%

Sample

1st row85123A
2nd row71053
3rd row84406B
4th row84029G
5th row84029E
ValueCountFrequency (%)
85123a2380
 
0.4%
224232203
 
0.4%
85099b2159
 
0.4%
475661727
 
0.3%
207251639
 
0.3%
848791502
 
0.3%
227201477
 
0.3%
221971476
 
0.3%
212121385
 
0.3%
207271350
 
0.2%
Other values (3949)524648
96.8%
2025-10-23T21:50:06.956240image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2828325
30.0%
1296053
 
10.7%
3259035
 
9.4%
8210898
 
7.7%
9201222
 
7.3%
0197322
 
7.2%
4186057
 
6.7%
7180372
 
6.5%
5180005
 
6.5%
6155713
 
5.6%
Other values (41)61605
 
2.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)2756607
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2828325
30.0%
1296053
 
10.7%
3259035
 
9.4%
8210898
 
7.7%
9201222
 
7.3%
0197322
 
7.2%
4186057
 
6.7%
7180372
 
6.5%
5180005
 
6.5%
6155713
 
5.6%
Other values (41)61605
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)2756607
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2828325
30.0%
1296053
 
10.7%
3259035
 
9.4%
8210898
 
7.7%
9201222
 
7.3%
0197322
 
7.2%
4186057
 
6.7%
7180372
 
6.5%
5180005
 
6.5%
6155713
 
5.6%
Other values (41)61605
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)2756607
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2828325
30.0%
1296053
 
10.7%
3259035
 
9.4%
8210898
 
7.7%
9201222
 
7.3%
0197322
 
7.2%
4186057
 
6.7%
7180372
 
6.5%
5180005
 
6.5%
6155713
 
5.6%
Other values (41)61605
 
2.2%
Distinct4223
Distinct (%)0.8%
Missing1454
Missing (%)0.3%
Memory size39.0 MiB
2025-10-23T21:50:07.200701image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length35
Median length28
Mean length26.64378
Min length1

Characters and Unicode

Total characters14399764
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique308 ?
Unique (%)0.1%

Sample

1st rowWHITE HANGING HEART T-LIGHT HOLDER
2nd rowWHITE METAL LANTERN
3rd rowCREAM CUPID HEARTS COAT HANGER
4th rowKNITTED UNION FLAG HOT WATER BOTTLE
5th rowRED WOOLLY HOTTIE WHITE HEART.
ValueCountFrequency (%)
set54599
 
2.3%
of53351
 
2.3%
bag51911
 
2.2%
red42902
 
1.8%
heart39163
 
1.7%
retrospot35126
 
1.5%
vintage33748
 
1.4%
design30066
 
1.3%
pink29526
 
1.2%
christmas25131
 
1.1%
Other values (2449)1973383
83.3%
2025-10-23T21:50:07.540155image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1966406
13.7%
E1288969
 
9.0%
A1093609
 
7.6%
T956778
 
6.6%
R918258
 
6.4%
O864963
 
6.0%
I788099
 
5.5%
S777550
 
5.4%
N716689
 
5.0%
L705042
 
4.9%
Other values (67)4323401
30.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)14399764
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1966406
13.7%
E1288969
 
9.0%
A1093609
 
7.6%
T956778
 
6.6%
R918258
 
6.4%
O864963
 
6.0%
I788099
 
5.5%
S777550
 
5.4%
N716689
 
5.0%
L705042
 
4.9%
Other values (67)4323401
30.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)14399764
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1966406
13.7%
E1288969
 
9.0%
A1093609
 
7.6%
T956778
 
6.6%
R918258
 
6.4%
O864963
 
6.0%
I788099
 
5.5%
S777550
 
5.4%
N716689
 
5.0%
L705042
 
4.9%
Other values (67)4323401
30.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)14399764
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1966406
13.7%
E1288969
 
9.0%
A1093609
 
7.6%
T956778
 
6.6%
R918258
 
6.4%
O864963
 
6.0%
I788099
 
5.5%
S777550
 
5.4%
N716689
 
5.0%
L705042
 
4.9%
Other values (67)4323401
30.0%

Quantity
Real number (ℝ)

Distinct722
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.5522495
Minimum-80995
Maximum80995
Zeros0
Zeros (%)0.0%
Negative10624
Negative (%)2.0%
Memory size4.1 MiB
2025-10-23T21:50:07.630726image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-80995
5-th percentile1
Q11
median3
Q310
95-th percentile29
Maximum80995
Range161990
Interquartile range (IQR)9

Descriptive statistics

Standard deviation218.08116
Coefficient of variation (CV)22.830346
Kurtosis119769.16
Mean9.5522495
Median Absolute Deviation (MAD)2
Skewness-0.26407631
Sum5176450
Variance47559.391
MonotonicityNot monotonic
2025-10-23T21:50:07.705763image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1148227
27.4%
281829
15.1%
1261063
11.3%
640868
 
7.5%
438484
 
7.1%
337121
 
6.9%
2424021
 
4.4%
1022288
 
4.1%
813129
 
2.4%
511757
 
2.2%
Other values (712)63122
11.6%
ValueCountFrequency (%)
-809951
< 0.1%
-742151
< 0.1%
-96002
< 0.1%
-93601
< 0.1%
-90581
< 0.1%
-53681
< 0.1%
-48301
< 0.1%
-36671
< 0.1%
-31671
< 0.1%
-31141
< 0.1%
ValueCountFrequency (%)
809951
< 0.1%
742151
< 0.1%
125401
< 0.1%
55681
< 0.1%
48001
< 0.1%
43001
< 0.1%
40001
< 0.1%
39061
< 0.1%
31861
< 0.1%
31142
< 0.1%
Distinct23260
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size4.1 MiB
Minimum2010-12-01 08:26:00
Maximum2011-12-09 12:50:00
Invalid dates0
Invalid dates (%)0.0%
2025-10-23T21:50:07.790224image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-10-23T21:50:07.870811image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

UnitPrice
Real number (ℝ)

Skewed 

Distinct1630
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6111136
Minimum-11062.06
Maximum38970
Zeros2515
Zeros (%)0.5%
Negative2
Negative (%)< 0.1%
Memory size4.1 MiB
2025-10-23T21:50:07.969362image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum-11062.06
5-th percentile0.42
Q11.25
median2.08
Q34.13
95-th percentile9.95
Maximum38970
Range50032.06
Interquartile range (IQR)2.88

Descriptive statistics

Standard deviation96.759853
Coefficient of variation (CV)20.984053
Kurtosis59005.719
Mean4.6111136
Median Absolute Deviation (MAD)1.23
Skewness186.50697
Sum2498804
Variance9362.4692
MonotonicityNot monotonic
2025-10-23T21:50:08.037888image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.2550496
 
9.3%
1.6538181
 
7.0%
0.8528497
 
5.3%
2.9527768
 
5.1%
0.4224533
 
4.5%
4.9519040
 
3.5%
3.7518600
 
3.4%
2.117697
 
3.3%
2.4617091
 
3.2%
2.0817005
 
3.1%
Other values (1620)283001
52.2%
ValueCountFrequency (%)
-11062.062
 
< 0.1%
02515
0.5%
0.0014
 
< 0.1%
0.011
 
< 0.1%
0.033
 
< 0.1%
0.0466
 
< 0.1%
0.06117
 
< 0.1%
0.079
 
< 0.1%
0.0856
 
< 0.1%
0.092
 
< 0.1%
ValueCountFrequency (%)
389701
 
< 0.1%
17836.461
 
< 0.1%
16888.021
 
< 0.1%
16453.711
 
< 0.1%
13541.333
< 0.1%
13474.791
 
< 0.1%
11586.51
 
< 0.1%
11062.061
 
< 0.1%
8286.221
 
< 0.1%
8142.752
< 0.1%

CustomerID
Real number (ℝ)

Missing 

Distinct4372
Distinct (%)1.1%
Missing135080
Missing (%)24.9%
Infinite0
Infinite (%)0.0%
Mean15287.691
Minimum12346
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 MiB
2025-10-23T21:50:08.122022image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum12346
5-th percentile12626
Q113953
median15152
Q316791
95-th percentile17905
Maximum18287
Range5941
Interquartile range (IQR)2838

Descriptive statistics

Standard deviation1713.6003
Coefficient of variation (CV)0.1120902
Kurtosis-1.1799824
Mean15287.691
Median Absolute Deviation (MAD)1481
Skewness0.02983499
Sum6.2194759 × 109
Variance2936426
MonotonicityNot monotonic
2025-10-23T21:50:08.288530image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
178417983
 
1.5%
149115903
 
1.1%
140965128
 
0.9%
127484642
 
0.9%
146062782
 
0.5%
153112491
 
0.5%
146462085
 
0.4%
130891857
 
0.3%
132631677
 
0.3%
142981640
 
0.3%
Other values (4362)370641
68.4%
(Missing)135080
 
24.9%
ValueCountFrequency (%)
123462
 
< 0.1%
12347182
< 0.1%
1234831
 
< 0.1%
1234973
< 0.1%
1235017
 
< 0.1%
1235295
< 0.1%
123534
 
< 0.1%
1235458
 
< 0.1%
1235513
 
< 0.1%
1235659
 
< 0.1%
ValueCountFrequency (%)
1828770
 
< 0.1%
18283756
0.1%
1828213
 
< 0.1%
182817
 
< 0.1%
1828010
 
< 0.1%
182789
 
< 0.1%
182779
 
< 0.1%
1827616
 
< 0.1%
1827422
 
< 0.1%
182733
 
< 0.1%

Country
Categorical

Imbalance 

Distinct38
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.2 MiB
United Kingdom
495478 
Germany
 
9495
France
 
8557
EIRE
 
8196
Spain
 
2533
Other values (33)
 
17650

Length

Max length20
Median length14
Mean length13.376203
Min length3

Characters and Unicode

Total characters7248685
Distinct characters41
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnited Kingdom
2nd rowUnited Kingdom
3rd rowUnited Kingdom
4th rowUnited Kingdom
5th rowUnited Kingdom

Common Values

ValueCountFrequency (%)
United Kingdom495478
91.4%
Germany9495
 
1.8%
France8557
 
1.6%
EIRE8196
 
1.5%
Spain2533
 
0.5%
Netherlands2371
 
0.4%
Belgium2069
 
0.4%
Switzerland2002
 
0.4%
Portugal1519
 
0.3%
Australia1259
 
0.2%
Other values (28)8430
 
1.6%

Length

2025-10-23T21:50:08.371119image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
united495546
47.7%
kingdom495478
47.7%
germany9495
 
0.9%
france8557
 
0.8%
eire8196
 
0.8%
spain2533
 
0.2%
netherlands2371
 
0.2%
belgium2069
 
0.2%
switzerland2002
 
0.2%
portugal1519
 
0.1%
Other values (35)10904
 
1.0%

Most occurring characters

ValueCountFrequency (%)
n1023046
14.1%
i1001404
13.8%
d998442
13.8%
e526754
7.3%
m507621
7.0%
t504192
7.0%
g499871
6.9%
o499396
6.9%
496761
6.9%
U496283
6.8%
Other values (31)694915
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)7248685
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n1023046
14.1%
i1001404
13.8%
d998442
13.8%
e526754
7.3%
m507621
7.0%
t504192
7.0%
g499871
6.9%
o499396
6.9%
496761
6.9%
U496283
6.8%
Other values (31)694915
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)7248685
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n1023046
14.1%
i1001404
13.8%
d998442
13.8%
e526754
7.3%
m507621
7.0%
t504192
7.0%
g499871
6.9%
o499396
6.9%
496761
6.9%
U496283
6.8%
Other values (31)694915
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)7248685
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n1023046
14.1%
i1001404
13.8%
d998442
13.8%
e526754
7.3%
m507621
7.0%
t504192
7.0%
g499871
6.9%
o499396
6.9%
496761
6.9%
U496283
6.8%
Other values (31)694915
9.6%

Interactions

2025-10-23T21:50:04.519370image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-10-23T21:50:03.573077image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-10-23T21:50:04.171888image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-10-23T21:50:04.618820image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-10-23T21:50:03.837217image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-10-23T21:50:04.323719image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-10-23T21:50:04.705461image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-10-23T21:50:04.088641image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2025-10-23T21:50:04.422258image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2025-10-23T21:50:08.423225image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
CountryCustomerIDQuantityUnitPrice
Country1.0000.3020.0420.006
CustomerID0.3021.000-0.141-0.013
Quantity0.042-0.1411.000-0.385
UnitPrice0.006-0.013-0.3851.000

Missing values

2025-10-23T21:50:04.924216image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2025-10-23T21:50:05.160936image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-10-23T21:50:05.519715image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

InvoiceNoStockCodeDescriptionQuantityInvoiceDateUnitPriceCustomerIDCountry
053636585123AWHITE HANGING HEART T-LIGHT HOLDER612/1/2010 8:262.5517850.0United Kingdom
153636571053WHITE METAL LANTERN612/1/2010 8:263.3917850.0United Kingdom
253636584406BCREAM CUPID HEARTS COAT HANGER812/1/2010 8:262.7517850.0United Kingdom
353636584029GKNITTED UNION FLAG HOT WATER BOTTLE612/1/2010 8:263.3917850.0United Kingdom
453636584029ERED WOOLLY HOTTIE WHITE HEART.612/1/2010 8:263.3917850.0United Kingdom
553636522752SET 7 BABUSHKA NESTING BOXES212/1/2010 8:267.6517850.0United Kingdom
653636521730GLASS STAR FROSTED T-LIGHT HOLDER612/1/2010 8:264.2517850.0United Kingdom
753636622633HAND WARMER UNION JACK612/1/2010 8:281.8517850.0United Kingdom
853636622632HAND WARMER RED POLKA DOT612/1/2010 8:281.8517850.0United Kingdom
953636784879ASSORTED COLOUR BIRD ORNAMENT3212/1/2010 8:341.6913047.0United Kingdom
InvoiceNoStockCodeDescriptionQuantityInvoiceDateUnitPriceCustomerIDCountry
54189958158722726ALARM CLOCK BAKELIKE GREEN412/9/2011 12:503.7512680.0France
54190058158722730ALARM CLOCK BAKELIKE IVORY412/9/2011 12:503.7512680.0France
54190158158722367CHILDRENS APRON SPACEBOY DESIGN812/9/2011 12:501.9512680.0France
54190258158722629SPACEBOY LUNCH BOX1212/9/2011 12:501.9512680.0France
54190358158723256CHILDRENS CUTLERY SPACEBOY412/9/2011 12:504.1512680.0France
54190458158722613PACK OF 20 SPACEBOY NAPKINS1212/9/2011 12:500.8512680.0France
54190558158722899CHILDREN'S APRON DOLLY GIRL612/9/2011 12:502.1012680.0France
54190658158723254CHILDRENS CUTLERY DOLLY GIRL412/9/2011 12:504.1512680.0France
54190758158723255CHILDRENS CUTLERY CIRCUS PARADE412/9/2011 12:504.1512680.0France
54190858158722138BAKING SET 9 PIECE RETROSPOT312/9/2011 12:504.9512680.0France

Duplicate rows

Most frequently occurring

InvoiceNoStockCodeDescriptionQuantityInvoiceDateUnitPriceCustomerIDCountry# duplicates
161355552422698PINK REGENCY TEACUP AND SAUCER16/5/2011 11:372.9516923.0United Kingdom20
161255552422697GREEN REGENCY TEACUP AND SAUCER16/5/2011 11:372.9516923.0United Kingdom12
320257286122775PURPLE DRAWERKNOB ACRYLIC EDWARDIAN1210/26/2011 12:461.2514102.0United Kingdom8
34753851421756BATH BUILDING BLOCK WORD112/12/2010 14:275.9515044.0United Kingdom6
47454052421756BATH BUILDING BLOCK WORD11/9/2011 12:535.9516735.0United Kingdom6
52854126621754HOME BUILDING BLOCK WORD11/16/2011 16:255.9515673.0United Kingdom6
52954126621755LOVE BUILDING BLOCK WORD11/16/2011 16:255.9515673.0United Kingdom6
3146572344MManual4810/24/2011 10:431.5014607.0United Kingdom6
424957828923395BELLE JARDINIERE CUSHION COVER111/23/2011 14:073.7517841.0United Kingdom6
18653722470007HI TEC ALPINE HAND WARMER112/5/2010 16:241.6513174.0United Kingdom5